CN108267106B - Quick, stable and simple cylindricity error evaluation method - Google Patents
Quick, stable and simple cylindricity error evaluation method Download PDFInfo
- Publication number
- CN108267106B CN108267106B CN201711489035.6A CN201711489035A CN108267106B CN 108267106 B CN108267106 B CN 108267106B CN 201711489035 A CN201711489035 A CN 201711489035A CN 108267106 B CN108267106 B CN 108267106B
- Authority
- CN
- China
- Prior art keywords
- serial number
- matrix
- analysis
- key
- elements
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/20—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring contours or curvatures, e.g. determining profile
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Complex Calculations (AREA)
Abstract
The invention belongs to the field of precision metering and computer application, and relates to a stable, quick and simple cylindricity error evaluation method, which comprises the following steps: step 1: acquiring a measuring point set, and establishing a characteristic row vector set, a boundary element set and a state element set according to the measuring point set; step 2: taking a measuring point corresponding to the minimum value of the state element set as a key point, and adding the measuring point serial number of the key point set into the key point set; and step 3: establishing an analysis matrix and an analysis column vector according to the key point set; and 4, step 4: performing rank analysis on the analysis matrix and the augmented analysis matrix to determine whether to continue optimizing, eliminating key points or terminating a program and obtain an optimal value; and 5: solving the analysis matrix and the analysis column vector to obtain an optimizing direction; step 6: solving a new key point by the tracing problem, updating a measuring point state set, and entering the next cycle; and 7, terminating the program and obtaining an optimal value.
Description
Technical Field
The invention belongs to the field of precision metering and computer application, and relates to a stable, quick and simple cylindricity error evaluation method, which can be used for evaluating the cylindricity error of parts with a revolving body structure and provides guidance for the improvement of the processing technology of the parts.
Background
The size error and the shape and position error (short for shape error and position error) directly influence the product quality, the assembly and the service life of the product, and the method has important significance for quickly and accurately calculating the part error. The definition and discrimination method of the cylindricity error are given in the national standard and the ISO standard, but the method of calculating the cylindricity error value from the measured data is not given. At present, the evaluation method of cylindricity error is a research hotspot of academia and is mainly divided into the following five evaluation methods.
First, a specialized geometric assessment method. And gradually searching for cylindricity errors meeting the definition and/or discrimination conditions of national standards and ISO standards according to the translation and deformation strategies of the inscribed cylinder and/or the circumscribed cylinder by utilizing the geometric properties of the cylinder. The method has high speed, but the form of the mathematical model is complex, and the method is not easy to popularize and use.
Second, convex hull or convex hull-like evaluation methods. And constructing a convex hull or a similar convex hull by using the properties of the convex hull, acquiring effective measurement data, reducing the scale of the data to be evaluated, and finally acquiring the cylindricity error meeting the definition and/or judgment conditions of the national standard and the ISO standard by using an enumeration method. This type of approach has significant advantages when dealing with medium scale station data. Even when the data size is large, the data size can still be reduced by constructing the convex hull. However, the efficiency of such methods for direct assessment has been inadequate.
And in the third category, a linear or nonlinear target optimization function is constructed, optimization solution is carried out by adopting a common optimization method, and the optimization value of the target optimization function is taken as a cylindricity error. The method is simple and easy to understand, and realizes a standard solution method in a plurality of software, so the method is easy to popularize. The method is generally inefficient because geometric characteristics of cylindricity error evaluation are not added and the condition that the data scale in the evaluation task is large is not considered.
The fourth category, artificial intelligence/biological intelligence algorithms. The advantage of this type of method over the third type of method is to analyze the "objective function with complex gradient or no apparent analytic expression" and to find the "global optimum". The method also realizes standard solutions in a plurality of software at present, so the method is easy to popularize. Although these methods are relatively hot at present, they are not suitable for use in error assessment of cylindricity. This is because the gradient of the objective function for cylindricity error assessment is the sum of a large number of simple analytical expressions, and the "local optimum" of the objective function is the "global optimum". Thus, this type of process does not have a significant advantage over the third type of process.
The fifth category, active set methods. The active set method is a method specially used for processing large-scale planning problems and is characterized in that the processing of 'invalid constraint' is reduced as much as possible in the optimization process. When the method is applied to cylindricity evaluation, the efficiency is equivalent to that of the first method, the algorithm maturity and the software integration are equivalent to that of the third method and the fourth method, and the method is a relatively quick and simple cylindricity error evaluation method at present. However, this method is very sensitive to the initial value and does not always perform the cylindricity error assessment task stably.
In summary, a stable, fast and simple method for evaluating cylindricity error is still lacking.
Disclosure of Invention
The purpose of the invention is:
aiming at the problems in the prior art, the invention provides a stable, quick and simple cylindricity error evaluation method, which can be used for evaluating the cylindricity error of parts with a revolving body structure and provides guidance for the improvement of the processing technology of the parts.
The scheme adopted by the invention is as follows:
a quick, stable and simple cylindricity error evaluation method is realized by the following steps:
step 1: obtaining a set of measurement pointsp i And according to ap i Establishing a characteristic line vector setA 𝛼 Great, boundary element setb 𝛼 Great Chinese character and state element sett 𝛼 }, wherein:
i=1, 2, 3, …, N；ξ=1, 2, 3, …, N, N+1, …,2N；ithe serial numbers of the measuring points are shown,Nthe total number of the measuring points is;
p i ={x i , y i , z i is the measurement pointiAnd the axis of the measured cylinder approaches the coordinate systemzThe central planes of the two bottom surfaces of the measured cylinder are close to the XOY plane of the coordinate system;
t i = t i+N =
all state elementst 𝛼 Is a set of state elementst 𝛼 }；
A i =- A i N+ =([x i /t i , y i /t i , -y i z i /t i , x i z i /t i , 1]) Is a feature row vector, all feature row vectorsA 𝛼 Is a set of characteristic line vectorsA 𝛼 }；
b i = b i+N =bIs a real number greater than 0, all boundary elementsb 𝛼 Set of (2)As a set of border elementsb 𝛼 }。
After step 1, step 2 is performed.
Step 2: gett i Minimum valuet min,inCorresponding serial numberl 1Is a key serial number, and willl 1Last page added to key serial number setlIn (1) }; gett i N+Maximum valuet max,outCorresponding serial numberl 2Is a key serial number, and willl 2Last page added to key serial number setlIn (c) }.
After step 2, step 3 is performed.
And step 3: according to the key sequence numberlEstablishment of an analysis matrixAAnd analyzing the column vectorsbWherein:
A=[…, A j T, …, A k T, …]Tis aLA matrix of rows and 5 columns,Lis a critical sequence number setlThe number of the elements in the (C),j, kis a critical sequence number setlThe elements in (1);
b=[…, b, …]Tis aLA column vector of rows.
After step 3, step 4 is performed.
And 4, step 4: for analysis matrixAAnd an augmented analysis matrixA, b]Rank analysis was performed.
Computingr A =rank(A)，r Ab =rank（[A, b]) And comparer A Andr Ab there are only two cases:
the first condition is as follows: if it is notr A =r Ab Then, the optimization should be continued, jumping to step 5;
case two: if it is notr A < r Ab Then, an attempt is made to determine from the analysis matrixAAnd analyzing the column vectorsbMiddle deleted key serial number setlOne of the elementslThe corresponding row of the image data is displayed,obtaining a reduced matrixA l- And reducing the column vectorb l- Solving a linear equationA l- v l- = b l- Solution of (2)v l- =v l-0 Then calculateb l- =A l v l-0 (ii) a If the key sequence number setlThe elements in (1) have all been tried and none have been obtainedb l- >bThen, the optimization should be ended, jumping to step 7; if the critical sequence number set is triedlElements in (b) }lWhen it is obtainedb l- >bThen, the matrix will be reducedA l- And reducing the column vectorb l- Respectively asAMatrix and analysis column vectorbWill elementlMovable key serial number setlAnd jumping to the step 5; wherein the content of the first and second substances,v l- =[v l-,1, v l-,2, v l-,3, v l-,4, v l-,5]T，v l-0 =[v l-0,1, v l-0,2, v l-0,3, v l-0,4, v l-0,5]T。
and 5: solving linear equationsAv= bSolution of (2)v=v 0 Wherein, in the step (A),v=[v 1, v 2, v 3, v 4, v 5]T，v 0 =[v 0,1, v 0,2, v 0,3, v 0,4, v 0,5]T。
after step 5, step 6 is performed.
Step 6: computingv 𝛼 =A 𝛼 v 0 Then calculateτ i =(t i – t min,in)÷(b - v i )，τ i N+ =( t max,out – t i+N )÷(b - v i+N ). Getτ 𝛼 Minimum value in the part of greater than zeroτ minCorresponding serial numberl 3Is a new key serial number and willl 3Last page added to key serial number setlIn (c) }.
All will bet i Is updated tot i + τ min∙(v i - v 0,5) All will bet i N+Is updated tot i N+-τ min∙( v i N++ v 0,5)，t min,inIs updated tot i The minimum value of (a) is determined,t max,outis updated tot i N+Is measured.
And finishing one-time optimization after the step 6 is finished, and performing the step 3.
And 7: computingt=t max,out- t min,in Is the error in cylindricity sought.
Conveniently obtaining the measuring point set in step 1p i A general measurement data can be preparedp i * Processing by, but not limited to, the following method, obtaining the axis close to the coordinate systemzMeasuring point collection for axis and two bottom surface central planes of measured cylinder near XOY plane of coordinate systemp i }: firstly, moving according to the average value of coordinates; moving according to the extreme value of the coordinate; and thirdly, moving according to the principle of minimum root mean square of the coordinates.
To get a more accurate solution, the following optimization can be done:
in step 6, ifτ min∙ v i Of single or several iterationsτ min∙ v i Greater than a given thresholdqThen, the measuring points are collectedp i Is updated top i + τ min∙vOrp i +∑τ min∙vAnd updating the characteristic line vector set according to the formula in the step oneA i Great, boundary element setb i Great Chinese character and state element sett i }。
To facilitate numerical calculation, can makebTaking a specific value greater than 0, but not limited to 1.
The invention has the beneficial effects that:
1. the geometric characteristics of the cylindricity error are fully considered, and the evaluation form is simplified, so that the method is easier to popularize than the first type of evaluation method. 2. The geometric characteristics of the cylindricity error are fully considered, a better value is obtained through mature linear operation in each iteration, and the minimum cylindricity error can be finally obtained, so that the algorithm is stable, and the problem of initial value sensitivity of the fifth method does not exist. 3. By implying the fact that most of the measuring points are invalid measuring points in the cylindricity error assessment, the invalid measuring points are not added with iteration, so that the iteration number of the method is less and is equivalent to that of the first type assessment method and the fifth type assessment method. 4. When calculating optimizing direction, only considering key sequence number setlAnd (4) corresponding measuring points, so that the operation amount of each iteration is small, and the method is equivalent to the fifth type evaluation method. 5. Because the iteration times are less and the operation amount of each iteration is less, the total operation speed is equivalent to the first type evaluation method and the fifth type evaluation method.
The invention provides a cylindricity error evaluation method which is stable, quick and simple in form, can be used for evaluating the cylindricity error of a part with a revolving body structure, and provides guidance for improvement of a processing process of the part, so that the method has industrial possibility.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The following are specific embodiments of the present invention, and the embodiments of the present invention will be further described with reference to the drawings, but the present invention is not limited to these embodiments.
Evaluation test setp i Cylindricity error of.
Step 1: obtaining a set of measurement pointsp i The method comprises the following steps:
| i | x i | y i | z i |
| 1 | 9.5285 | 3.1018 | -44.9417 |
| 2 | 5.8950 | -8.0895 | -39.9115 |
| 3 | -5.8697 | -8.0894 | -34.9254 |
| 4 | -9.5075 | 3.0930 | -29.9394 |
| 5 | 0.0051 | 10.0065 | -24.9598 |
| 6 | 9.5187 | 3.0979 | -19.9390 |
| 7 | 5.8812 | -8.0864 | -14.9905 |
| 8 | -5.8714 | -8.0748 | -9.9766 |
| 9 | -9.4958 | 3.1040 | -4.9176 |
| 10 | 0.0166 | 10.0059 | 0.0309 |
| 11 | 9.5210 | 3.0967 | 5.0832 |
| 12 | 5.8941 | -8.0790 | 10.0263 |
| 13 | -5.8642 | -8.0855 | 15.0456 |
| 14 | -9.5029 | 3.1009 | 20.0992 |
| 15 | 0.0151 | 10.0196 | 25.0235 |
| 16 | 9.5211 | 3.0912 | 30.0757 |
| 17 | 5.8899 | -8.0730 | 35.0988 |
| 18 | -5.8593 | -8.0820 | 40.0000 |
| 19 | -9.4997 | 3.0943 | 45.0219 |
| 20 | 0.0065 | 10.0019 | 50.0748 |
establishing a set of state elementst 𝛼 The method comprises the following steps:
| 𝛼 | 𝛼 | t 𝛼 |
| 1 | 21 | 10.0207 |
| 2 | 22 | 10.0095 |
| 3 | 23 | 9.9946 |
| 4 | 24 | 9.9980 |
| 5 | 25 | 10.0065 |
| 6 | 26 | 10.0101 |
| 7 | 27 | 9.9989 |
| 8 | 28 | 9.9838 |
| 9 | 29 | 9.9902 |
| 10 | 30 | 10.0059 |
| 11 | 31 | 10.0120 |
| 12 | 32 | 10.0006 |
| 13 | 33 | 9.9882 |
| 14 | 34 | 9.9960 |
| 15 | 35 | 10.0196 |
| 16 | 36 | 10.0104 |
| 17 | 37 | 9.9933 |
| 18 | 38 | 9.9825 |
| 19 | 39 | 9.9910 |
| 20 | 40 | 10.0019 |
establishing a characteristic row vectorCollection checkA 𝛼 }，ξ=iAt last, aA i The method comprises the following steps:
ξ=iat the time of +20, the number of the holes,A i+20=-A i 。
establishing a set of boundary elementsb 𝛼 The method comprises the following steps:
{b 𝛼 }=[1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1, 1,1,1,1,1,1,1,1,1,1]T。
after step 1, step 2 is performed.
Step 2: gett i Minimum valuet min,inThe corresponding serial number 18 is the key serial number, and 18 is added to the key serial number setlIn (1) }; gett i+20Maximum valuet max,outThe corresponding serial number 21 is the key serial number, and 21 is added into the key serial number setlChinese, a large aperturel}={18,21}；。
After step 2, step 3 is performed.
And step 3: according to the key sequence numberlEstablishment of an analysis matrixAAnd analyzing the column vectorsbWherein:
A= matrix of 2 rows and 5 columns, critical sequence number setlThe number of elements in = {18,21} is 2, and the elements are 18, 21;
b=[1,1]Tand is a 2-row column vector.
After step 3, step 4 is performed.
And 4, step 4: for analysis matrixAAnd an augmented analysis matrixA, b]Rank analysis was performed.
Computingr A =rank(A) =2，r Ab =rank（[A, b]) =2, and comparingr A Andr Ab . Because of the fact thatr A =r Ab So the seek should continue jumping to step 5.
And 5: solving linear equationsAv= bSolution of (2)v=v 0 =[0.0000 , 0.0000 , 0.0626 , 0.0438 , 0.0000]T。
After step 5, step 6 is performed.
Step 6: computingv 𝛼 =A 𝛼 v 0 ，ξ=iThe results are as follows:
| i | v i |
| 1 | -1.0000 |
| 2 | -3.0491 |
| 3 | -0.8721 |
| 4 | 1.8266 |
| 5 | 1.5625 |
| 6 | -0.4438 |
| 7 | -1.1453 |
| 8 | -0.2484 |
| 9 | 0.3003 |
| 10 | -0.0019 |
| 11 | 0.1132 |
| 12 | 0.7660 |
| 13 | 0.3759 |
| 14 | -1.2271 |
| 15 | -1.5654 |
| 16 | 0.6709 |
| 17 | 2.6814 |
| 18 | 1.0000 |
| 19 | -2.7476 |
| 20 | -3.1344 |
ξ=iat the time of +20, the number of the holes,v i+20=-v i 。
then calculateτ i =(t i – t min,in)÷(b - v i )，τ i+10 =( t max,out – t i+10)÷(b - v i+10). Getτ 𝛼 The results for the portion of the series greater than zero are as follows:
| 𝛼 | τ 𝛼 |
| 1 | 0.0191 |
| 2 | 0.0067 |
| 3 | 0.0065 |
| 6 | 0.0192 |
| 7 | 0.0077 |
| 8 | 0.0010 |
| 9 | 0.0111 |
| 10 | 0.0234 |
| 11 | 0.0333 |
| 12 | 0.0773 |
| 13 | 0.0092 |
| 14 | 0.0061 |
| 15 | 0.0145 |
| 16 | 0.0848 |
| 19 | 0.0023 |
| 20 | 0.0047 |
| 23 | 0.2034 |
| 24 | 0.0080 |
| 25 | 0.0055 |
| 26 | 0.0189 |
| 28 | 0.0491 |
| 29 | 0.0234 |
| 30 | 0.0148 |
| 31 | 0.0078 |
| 32 | 0.0114 |
| 33 | 0.0236 |
| 36 | 0.0061 |
| 37 | 0.0074 |
| 38 | 0.0191 |
minimum value thereofτ minThe corresponding serial number 8 is a new key serial number, and 8 is added into the key serial number setlIn (c) }. At this moment, the openingl}={18,21,8}。
All will bet i Is updated tot i + τ min∙(v i - v 0,5)= t i + τ min∙(v i -0), mixing allt i+20Is updated tot i+20-τ min∙( v i+20+ v 0,5)= t i+20-τ min∙( v i+20+0)，t min,inIs updated tot i The minimum value of (a) is determined,t max,outis updated tot i+20Is measured.
And finishing one-time optimization after the step 6 is finished, and performing the step 3.
By analogy, after the sixth optimization, the key sequence number is collectedl} ={18,19,35,20,22,23}。
At this time, step 3 is performed first: according to the key sequence numberl} = {18,19,35,20,22,23} building analysis matricesAAnd analyzing the column vectorsbWherein:
b=[1,1,1,1,1,1]T。
after step 3, step 4 is performed.
And 4, step 4: for analysis matrixAAnd an augmented analysis matrixA, b]Rank analysis was performed.
Computingr A =rank(A) =5，r Ab =rank（[A, b]）=6， r A < r Ab . First, an attempt is made to analyze the matrix fromAAnd analyzing the column vectorsbMiddle deleted key serial number setl}={1819,35,20,22,23} resulting in a reduced matrixA -18：
Andb -18column vectorb -18=[1,1,1,1,1]T。
Solving a linear equationA -18 v -18= b -18Solution of (2)v -18=v -018=[-1.6091 , 0.2620 , -0.0798 , -0.0358 , -3.2544]TThen calculateb -18=A 18 v -018= -4.2658 <1=b；b -19= 10.3093 >1=b。
Will be provided withA -19Matrix sumb -19The matrices are respectively asAMatrix andbmatrix, moving element 19 out of the set of key sequence numbersl}, makingl} = {18, 35,20,22,23}, and jumps to step 5.
By analogy, after the seventh optimization, the key sequence number is collectedl} ={18, 35, 20, 22, 23, 17}。
At this time, step 3 is performed first: according to the key sequence numberl} = {18, 35,20,22,23, 17} building analysis matricesAAnd analyzing the column vectorsb。
After step 3, step 4 is performed.
And 4, step 4: for analysis matrixAAnd an augmented analysis matrixA, b]Rank analysis was performed.
Computingr A =rank(A) =5，r Ab =rank（[A, b]）=6， r A < r Ab 。
Corresponding checkl} = {18, 35,20,22,23, 17}, and each is obtainedb -18= -12.6721 <1=b，b -35=-1.8263<1=b，b -20= -1.8264 <1=b，b -22= -12.7279 <1=b，b -23=-12.6335 <1=b，b -17= -12.6883<1=b. Jump to step 7.
And 7: computingt=t max,out- t min,in = 0.0334 is the cylindricity error sought.
In the above description, the present invention has been described by way of specific embodiments, but those skilled in the art will appreciate that various modifications and variations can be made within the spirit and scope of the invention as hereinafter claimed.
Claims (5)
1. A quick, stable and simple cylindricity error evaluation method is characterized by comprising the following steps:
step 1: obtaining a set of measurement pointsp i And according to ap i Establishing a characteristic line vector setA 𝛼 Great, boundary element setb 𝛼 Great Chinese character and state element sett 𝛼 }, wherein:
i=1, 2, 3, …, N；ξ=1, 2, 3, …, N, N+1, …,2N；ithe serial numbers of the measuring points are shown,Nthe total number of the measuring points is;
p i ={x i , y i , z i is the measurement pointiAnd the axis of the measured cylinder approaches the coordinate systemzThe central planes of the two bottom surfaces of the measured cylinder are close to the XOY plane of the coordinate system;
t i = t i+N =
all state elementst 𝛼 Is a set of state elementst 𝛼 }；
A i =- A i N+ =([x i /t i , y i /t i , -y i z i /t i , x i z i /t i , 1]) Is a feature row vector, all feature row vectorsA 𝛼 Is a set of characteristic line vectorsA 𝛼 }；
b i = b i+N =bIs a real number greater than 0, all boundary elementsb 𝛼 Is a set of boundary elementsb 𝛼 }；
After the step 1 is finished, performing a step 2;
step 2: gett i Minimum valuet min,inCorresponding serial numberl 1Is a key serial number, and willl 1Last page added to key serial number setlIn (1) }; gett i N+Maximum valuet max,outCorresponding serial numberl 2Is a key serial number, and willl 2Last page added to key serial number setlIn (1) };
step 3 is carried out after step 2 is finished;
and step 3: according to the key sequence numberlEstablishment of an analysis matrixAAnd analyzing the column vectorsbWherein:
A=[…, A j T, …, A k T, …]Tis aLA matrix of rows and 5 columns,Lis a critical sequence number setlThe number of the elements in the (C),j, kis a critical sequence number setlThe elements in (1);
b=[…, b, …]Tis aLA column vector of rows;
step 4 is carried out after step 3 is finished;
and 4, step 4: for analysis matrixAAnd an augmented analysis matrixA, b]Performing rank analysis;
computingr A =rank(A)，r Ab =rank（[A, b]) And comparer A Andr Ab there are only two cases:
the first condition is as follows: if it is notr A =r Ab Then, the optimization should be continued, jumping to step 5;
case two: if it is notr A < r Ab Then, an attempt is made to determine from the analysis matrixAAnd analyzing the column vectorsbMiddle deleted key serial number setlOne of the elementslCorresponding rows, obtaining a reduced matrixA l- And reducing the column vectorb l- Solving a linear equationA l- v l- = b l- Solution of (2)v l- =v l-0 Then calculateb l- =A l v l-0 (ii) a If the key sequence number setlThe elements in (1) have all been tried and none have been obtainedb l- >bThen, the optimization should be ended, jumping to step 7; if the critical sequence number set is triedlElements in (b) }lWhen it is obtainedb l- >bThen, the matrix will be reducedA l- And reducing the column vectorb l- Respectively asAMatrix and analysis column vectorbWill elementlMovable key serial number setlAnd jumping to the step 5; wherein the content of the first and second substances,v l- =[v l-,1, v l-,2, v l-,3, v l-,4, v l-,5]T，v l-0 =[v l-0,1, v l-0,2, v l-0,3, v l-0,4, v l-0,5]T；
and 5: solving linear equationsAv= bSolution of (2)v=v 0 Wherein, in the step (A),v=[v 1, v 2, v 3, v 4, v 5]T，v 0 =[v 0,1, v 0,2, v 0,3, v 0,4, v 0,5]T；
step 6 is carried out after step 5 is finished;
step 6: computingv 𝛼 =A 𝛼 v 0 Then calculateτ i =(t i – t min,in)÷(b - v i )，τ i N+ =( t max,out – t i+N )÷(b -v i+N ) (ii) a Getτ 𝛼 Minimum value in the part of greater than zeroτ minCorresponding serial numberl 3Is a new key serial number and willl 3Last page added to key serial number setlIn (1) };
all will bet i Is updated tot i + τ min∙(v i - v 0,5) All will bet i N+Is updated tot i N+-τ min∙( v i+N + v 0,5)，t min,inIs updated tot i The minimum value of (a) is determined,t max,outis updated tot i N+Maximum value of (d);
finishing one-time optimization after the step 6 is finished, and performing the step 3;
and 7: computingt=t max,out- t min,in Is the error in cylindricity sought.
2. A method for fast and simple cylindricity error assessment according to claim 1, characterized in that the method is to be used for evaluating cylindricity errorsGeneral measurement datap i * Obtaining the axis close to the coordinate system by conventional coordinate transformationzMeasuring point collection for axis and two bottom surface central planes of measured cylinder near XOY plane of coordinate systemp i }。
3. A fast and simple cylindricity error assessment method according to claim 2, characterized in that said conventional coordinate transformation is one, moving according to the mean value of the coordinates, or two, moving according to the extreme values of the coordinates, or three, moving according to the root mean square minimum principle of the coordinates.
4. A fast and simple cylindricity error assessment method according to claim 1, characterized in that in step 6, if it is, theτ min∙ v i Of single or several iterationsτ min∙ v i Greater than a given thresholdqThen, the measuring points are collectedp i Is updated top i + τ min∙vOrp i +∑τ min∙vAnd updating the characteristic line vector set according to the formula in the step oneA i Great, boundary element setb i Great Chinese character and state element sett i }。
5. A fast and simple cylindricity error assessment method according to claim 1,b=1。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711489035.6A CN108267106B (en) | 2017-12-30 | 2017-12-30 | Quick, stable and simple cylindricity error evaluation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711489035.6A CN108267106B (en) | 2017-12-30 | 2017-12-30 | Quick, stable and simple cylindricity error evaluation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108267106A CN108267106A (en) | 2018-07-10 |
| CN108267106B true CN108267106B (en) | 2020-11-27 |
Family
ID=62772905
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711489035.6A Expired - Fee Related CN108267106B (en) | 2017-12-30 | 2017-12-30 | Quick, stable and simple cylindricity error evaluation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108267106B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110285781B (en) * | 2019-07-10 | 2023-09-29 | 桂林电子科技大学 | Rapid assessment method for plane parallelism relative to reference plane |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH01161156A (en) * | 1987-12-17 | 1989-06-23 | Mitsubishi Heavy Ind Ltd | Measuring method for rotary motion accuracy |
| CN102982240B (en) * | 2012-11-19 | 2016-01-06 | 华侨大学 | Based on the Circularity error evaluation method of mutative scale Chaos-Annealing |
| CN103256916B (en) * | 2013-06-10 | 2015-07-08 | 陈磊磊 | Evaluation method of part flatness error based on minimum area |
| CN103278126B (en) * | 2013-06-11 | 2015-09-30 | 陈磊磊 | A kind of sphericity error assessment method for part based on Minimum Area |
| CN103292773B (en) * | 2013-06-18 | 2015-11-25 | 桂林电子科技大学 | A kind of symmetry error evaluation method based on Minimum Area |
| CN103292769B (en) * | 2013-06-19 | 2015-11-25 | 桂林电子科技大学 | A kind of plane inclination error detection method based on Minimum Area |
| CN104482911B (en) * | 2014-12-12 | 2017-08-11 | 燕山大学 | Sphericity error assessment method based on error ball |
| CN105157655A (en) * | 2015-05-11 | 2015-12-16 | 王灿 | Roundness error quick evaluation method based on regional search |
| CN105841640B (en) * | 2016-04-29 | 2018-09-18 | 北京航空航天大学 | flatness error evaluation method and device |
| CN106971087A (en) * | 2017-05-26 | 2017-07-21 | 上海大学 | A kind of Flatness error evaluation method based on secondary learning aid algorithm of climbing the mountain |
-
2017
- 2017-12-30 CN CN201711489035.6A patent/CN108267106B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN108267106A (en) | 2018-07-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110285781B (en) | Rapid assessment method for plane parallelism relative to reference plane | |
| CN102693452A (en) | Multiple-model soft-measuring method based on semi-supervised regression learning | |
| CN107885971B (en) | Method for identifying key protein by adopting improved flower pollination algorithm | |
| CN111488498A (en) | Node-graph cross-layer graph matching method and system based on graph neural network | |
| CN109931903A (en) | A kind of cylindricity assessment method based on improvement whale optimization algorithm | |
| US7587280B2 (en) | Genomic data mining using clustering logic and filtering criteria | |
| CN108267106B (en) | Quick, stable and simple cylindricity error evaluation method | |
| CN108286957A (en) | A kind of Flatness error evaluation method of fast steady letter | |
| CN112686881B (en) | Particle material mixing uniformity detection method based on image statistical characteristics and LSTM composite network | |
| CN110097922B (en) | Hierarchical TADs (TADs-related analysis) difference analysis method in Hi-C contact matrix based on online machine learning | |
| CN110739028B (en) | Cell line drug response prediction method based on K-nearest neighbor constraint matrix decomposition | |
| CN109166128B (en) | Non-equivalent three-dimensional point cloud segmentation method | |
| CN113884059A (en) | Single-datum plane shaft hole part gradient evaluation method based on rank analysis | |
| CN113192122A (en) | Optical center extraction method in visual detection process of assembly pose of large equipment | |
| CN112212758A (en) | Method for evaluating digitalized common reference radial total run-out error | |
| Freedman et al. | Revealing cell-fate bifurcations from transcriptomic trajectories of hematopoiesis | |
| CN110595424A (en) | Method for evaluating straightness in any direction based on digital gauge | |
| CN108253917A (en) | A kind of minimum circumscribed cylinder diameter assessment method of fast steady letter | |
| CN110619139A (en) | Rapid position degree evaluation method based on single-datum hole shaft part | |
| CN113483660A (en) | Method for evaluating radial circular run-out error of optical axis | |
| CN113483721A (en) | Method for rapidly evaluating straightness in any direction by applying maximum entity requirement | |
| CN113945130A (en) | Method for evaluating radial circular run-out error of stepped shaft | |
| Yu et al. | CNLLRR: a novel low-rank representation method for single-cell RNA-seq data analysis | |
| CN108562258A (en) | A kind of maximum inscribed circle column diameter assessment method of fast steady letter | |
| CN113932754A (en) | Method for quickly evaluating verticality of error measurement workpiece based on single reference plane |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20201116 Address after: 541004 the Guangxi Zhuang Autonomous Region golden Guilin Qixing District Road No. 1 Applicant after: GUILIN University OF ELECTRONIC TECHNOLOGY Address before: 541001 2 11-1, Longshan lane, Lingui District, Guilin, the Guangxi Zhuang Autonomous Region Applicant before: Tang Zhemin |
|
| TA01 | Transfer of patent application right | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20201127 Termination date: 20211230 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |